Tom Willis WV US Inactive
Tom Willis Victory
Shelley Joins Dems to Defund ICE
Ad copy
Just read the troubling news that Senator Shelley Moore Capito is working with Democrats on efforts to defund ICE, something many here in Parkersburg believe would make our communities less safe. We had a townhall at Cheryl’s Country Diner, visiting with folks about the issues surrounding West Virginia. Securing our nation’s borders and restoring safety at home must be a priority. I’ll always stand to protect our state and country. A nation without borders isn't a nation, and West Virginians deserve better than this.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 45.2/100 |
| Spend / Reach / Long. / Eff. | 34.7 · 76.3 · 4.1 · 65.6 |
| Spend range | USD 1,000–1,499 |
| Impressions | 90,000 – 99,999 |
| CPM (≈ $/1k impr) | USD 13.15 |
| Est. audience size | 100,001 – 500,000 |
| Days live | 16 (2026-03-18 → 2026-04-03) |
| Created | 2026-03-18 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | WV — Tom Willis |
| Surfaced by | “senate:Tom Willis” |
🧠 AI analysis
| Issue | immigration |
| Framing | attack opponent |
| Message type | persuasion |
| Emotional appeal | fear |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | border, none |
| Call to action | none |
| Standout element | Candidate holding up a local newspaper (Parkersburg News & Sentinel) as physical proof of the opponent's betrayal |
| Tactic | The newspaper prop functions as borrowed credibility, lending journalistic authority to the attack claim that incumbent Senator Capito is working with Democrats to defund ICE, framing her as a traitor to West Virginia values on immigration and public safety. |
Where it ran (delivery by region)
| West Virginia | 91.7% |
| Virginia | 3.3% |
| Maryland | 2.1% |
| Ohio | 1.5% |
| Kentucky | 1.4% |
| Pennsylvania | 0.0% |
Who saw it (delivery)
| 18-24 · female | 0.2% |
| 45-54 · male | 7.4% |
| 65+ · male | 16.7% |
| 65+ · female | 29.6% |
| 55-64 · unknown | 0.1% |
| 55-64 · male | 11.3% |
| 55-64 · female | 13.3% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 6.1% |
| 18-24 · male | 1.0% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 5.5% |
| 35-44 · female | 3.5% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 3.3% |
| 25-34 · female | 1.4% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.3% |
